{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "executionInfo": {
     "elapsed": 8251,
     "status": "ok",
     "timestamp": 1650011468229,
     "user": {
      "displayName": "Sam Lu",
      "userId": "15789059763790170725"
     },
     "user_tz": -480
    },
    "id": "BQXVYW2T_DcQ"
   },
   "outputs": [],
   "source": [
    "import gym\n",
    "import torch\n",
    "import torch.nn.functional as F\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from tqdm import tqdm\n",
    "import rl_utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "executionInfo": {
     "elapsed": 7,
     "status": "ok",
     "timestamp": 1650011468231,
     "user": {
      "displayName": "Sam Lu",
      "userId": "15789059763790170725"
     },
     "user_tz": -480
    },
    "id": "ClM8RKjB_DcR"
   },
   "outputs": [],
   "source": [
    "class PolicyNet(torch.nn.Module):\n",
    "    def __init__(self, state_dim, hidden_dim, action_dim):\n",
    "        super(PolicyNet, self).__init__()\n",
    "        self.fc1 = torch.nn.Linear(state_dim, hidden_dim)\n",
    "        self.fc2 = torch.nn.Linear(hidden_dim, action_dim)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = F.relu(self.fc1(x))\n",
    "        return F.softmax(self.fc2(x), dim=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "executionInfo": {
     "elapsed": 6,
     "status": "ok",
     "timestamp": 1650011468231,
     "user": {
      "displayName": "Sam Lu",
      "userId": "15789059763790170725"
     },
     "user_tz": -480
    },
    "id": "w0W82SjM_DcS"
   },
   "outputs": [],
   "source": [
    "class REINFORCE:\n",
    "    def __init__(self, state_dim, hidden_dim, action_dim, learning_rate, gamma,\n",
    "                 device):\n",
    "        self.policy_net = PolicyNet(state_dim, hidden_dim,\n",
    "                                    action_dim).to(device)\n",
    "        self.optimizer = torch.optim.Adam(self.policy_net.parameters(),\n",
    "                                          lr=learning_rate)  # 使用Adam优化器\n",
    "        self.gamma = gamma  # 折扣因子\n",
    "        self.device = device\n",
    "\n",
    "    def take_action(self, state):  # 根据动作概率分布随机采样\n",
    "        state = torch.tensor([state], dtype=torch.float).to(self.device)\n",
    "        probs = self.policy_net(state)\n",
    "        action_dist = torch.distributions.Categorical(probs)\n",
    "        action = action_dist.sample()\n",
    "        return action.item()\n",
    "\n",
    "    def update(self, transition_dict):\n",
    "        reward_list = transition_dict['rewards']\n",
    "        state_list = transition_dict['states']\n",
    "        action_list = transition_dict['actions']\n",
    "\n",
    "        G = 0\n",
    "        self.optimizer.zero_grad()\n",
    "        for i in reversed(range(len(reward_list))):  # 从最后一步算起\n",
    "            reward = reward_list[i]\n",
    "            state = torch.tensor([state_list[i]],\n",
    "                                 dtype=torch.float).to(self.device)\n",
    "            action = torch.tensor([action_list[i]]).view(-1, 1).to(self.device)\n",
    "            log_prob = torch.log(self.policy_net(state).gather(1, action))\n",
    "            G = self.gamma * G + reward\n",
    "            loss = -log_prob * G  # 每一步的损失函数\n",
    "            loss.backward()  # 反向传播计算梯度\n",
    "        self.optimizer.step()  # 梯度下降"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 102519,
     "status": "ok",
     "timestamp": 1650011570745,
     "user": {
      "displayName": "Sam Lu",
      "userId": "15789059763790170725"
     },
     "user_tz": -480
    },
    "id": "WeykNnJM_DcT",
    "outputId": "bed6d0bb-f499-4611-b74d-dee1959d8c06"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_44288\\4125764203.py:12: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at C:\\actions-runner\\_work\\pytorch\\pytorch\\builder\\windows\\pytorch\\torch\\csrc\\utils\\tensor_new.cpp:281.)\n",
      "  state = torch.tensor([state], dtype=torch.float).to(self.device)\n",
      "Iteration 0: 100%|███████████████████████████████████████| 100/100 [00:03<00:00, 28.10it/s, episode=100, return=40.800]\n",
      "Iteration 1: 100%|███████████████████████████████████████| 100/100 [00:05<00:00, 18.20it/s, episode=200, return=81.000]\n",
      "Iteration 2: 100%|██████████████████████████████████████| 100/100 [00:11<00:00,  9.08it/s, episode=300, return=163.100]\n",
      "Iteration 3: 100%|██████████████████████████████████████| 100/100 [00:14<00:00,  6.80it/s, episode=400, return=180.400]\n",
      "Iteration 4: 100%|██████████████████████████████████████| 100/100 [00:17<00:00,  5.85it/s, episode=500, return=182.400]\n",
      "Iteration 5: 100%|██████████████████████████████████████| 100/100 [00:16<00:00,  6.09it/s, episode=600, return=171.500]\n",
      "Iteration 6: 100%|██████████████████████████████████████| 100/100 [00:18<00:00,  5.55it/s, episode=700, return=172.400]\n",
      "Iteration 7: 100%|██████████████████████████████████████| 100/100 [00:19<00:00,  5.20it/s, episode=800, return=180.900]\n",
      "Iteration 8: 100%|██████████████████████████████████████| 100/100 [00:20<00:00,  4.97it/s, episode=900, return=200.000]\n",
      "Iteration 9: 100%|█████████████████████████████████████| 100/100 [00:21<00:00,  4.73it/s, episode=1000, return=200.000]\n"
     ]
    }
   ],
   "source": [
    "learning_rate = 1e-3\n",
    "num_episodes = 1000\n",
    "hidden_dim = 128\n",
    "gamma = 0.98\n",
    "device = torch.device(\"cuda\") if torch.cuda.is_available() else torch.device(\n",
    "    \"cpu\")\n",
    "\n",
    "env_name = \"CartPole-v0\"\n",
    "env = gym.make(env_name)\n",
    "env.seed(0)\n",
    "torch.manual_seed(0)\n",
    "state_dim = env.observation_space.shape[0]\n",
    "action_dim = env.action_space.n\n",
    "agent = REINFORCE(state_dim, hidden_dim, action_dim, learning_rate, gamma,\n",
    "                  device)\n",
    "\n",
    "return_list = []\n",
    "for i in range(10):\n",
    "    with tqdm(total=int(num_episodes / 10), desc='Iteration %d' % i) as pbar:\n",
    "        for i_episode in range(int(num_episodes / 10)):\n",
    "            episode_return = 0\n",
    "            transition_dict = {\n",
    "                'states': [],\n",
    "                'actions': [],\n",
    "                'next_states': [],\n",
    "                'rewards': [],\n",
    "                'dones': []\n",
    "            }\n",
    "            state = env.reset()\n",
    "            done = False\n",
    "            while not done:\n",
    "                action = agent.take_action(state)\n",
    "                next_state, reward, done, _ = env.step(action)\n",
    "                transition_dict['states'].append(state)\n",
    "                transition_dict['actions'].append(action)\n",
    "                transition_dict['next_states'].append(next_state)\n",
    "                transition_dict['rewards'].append(reward)\n",
    "                transition_dict['dones'].append(done)\n",
    "                state = next_state\n",
    "                episode_return += reward\n",
    "            return_list.append(episode_return)\n",
    "            agent.update(transition_dict)\n",
    "            if (i_episode + 1) % 10 == 0:\n",
    "                pbar.set_postfix({\n",
    "                    'episode':\n",
    "                    '%d' % (num_episodes / 10 * i + i_episode + 1),\n",
    "                    'return':\n",
    "                    '%.3f' % np.mean(return_list[-10:])\n",
    "                })\n",
    "            pbar.update(1)\n",
    "\n",
    "# Iteration 0: 100%|██████████| 100/100 [00:04<00:00, 23.88it/s, episode=100,\n",
    "# return=55.500]\n",
    "# Iteration 1: 100%|██████████| 100/100 [00:08<00:00, 10.45it/s, episode=200,\n",
    "# return=75.300]\n",
    "# Iteration 2: 100%|██████████| 100/100 [00:16<00:00,  4.75it/s, episode=300,\n",
    "# return=178.800]\n",
    "# Iteration 3: 100%|██████████| 100/100 [00:20<00:00,  4.90it/s, episode=400,\n",
    "# return=164.600]\n",
    "# Iteration 4: 100%|██████████| 100/100 [00:21<00:00,  4.58it/s, episode=500,\n",
    "# return=156.500]\n",
    "# Iteration 5: 100%|██████████| 100/100 [00:21<00:00,  4.73it/s, episode=600,\n",
    "# return=187.400]\n",
    "# Iteration 6: 100%|██████████| 100/100 [00:22<00:00,  4.40it/s, episode=700,\n",
    "# return=194.500]\n",
    "# Iteration 7: 100%|██████████| 100/100 [00:23<00:00,  4.24it/s, episode=800,\n",
    "# return=200.000]\n",
    "# Iteration 8: 100%|██████████| 100/100 [00:23<00:00,  4.33it/s, episode=900,\n",
    "# return=200.000]\n",
    "# Iteration 9: 100%|██████████| 100/100 [00:22<00:00,  4.14it/s, episode=1000,\n",
    "# return=186.100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 573
    },
    "executionInfo": {
     "elapsed": 1119,
     "status": "ok",
     "timestamp": 1650011571858,
     "user": {
      "displayName": "Sam Lu",
      "userId": "15789059763790170725"
     },
     "user_tz": -480
    },
    "id": "09ibOQwF_DcU",
    "outputId": "8762c94b-cc26-458a-cb3d-d1bb6b105089"
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "episodes_list = list(range(len(return_list)))\n",
    "plt.plot(episodes_list, return_list)\n",
    "plt.xlabel('Episodes')\n",
    "plt.ylabel('Returns')\n",
    "plt.title('REINFORCE on {}'.format(env_name))\n",
    "plt.show()\n",
    "\n",
    "mv_return = rl_utils.moving_average(return_list, 9)\n",
    "plt.plot(episodes_list, mv_return)\n",
    "plt.xlabel('Episodes')\n",
    "plt.ylabel('Returns')\n",
    "plt.title('REINFORCE on {}'.format(env_name))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "第9章-策略梯度算法.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python [conda env:RL]",
   "language": "python",
   "name": "conda-env-RL-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.20"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
